Run ❯ Get your own Python server Result Size: 785 x 1445 import pandas as pd calories = {"day1": 420, "day2": 380, "day3": 390} myvar = pd.Series(calories, index = ["day1", "day2"]) print(myvar) day1 420 day2 380 dtype: int64 ...
Single index for one row [1] returns a Pandas Series.A list of indexes [[0, 2]] returns a Pandas DataFrame.❮ DataFrame Reference Track your progress - it's free! Log in Sign Up COLOR PICKER PLUS SPACES GET CERTIFIED FOR TEACHERS FOR BUSINESS CONTACT US Top Tutorials HTML Tutorial ...
import pandas as pddata = { "x": [50, 40, 30], "y": [300, 1112, 42]}df = pd.DataFrame(data)x = df.agg(["sum"])print(x) Try it Yourself » Definition and UsageThe agg() method allows you to apply a function or a list of function names to be executed along one of ...
If you specify only one column, the return value is a Pandas Series object.To specify more than one column, specify the columns inside an array. The result will be a new DataFrame object.Syntaxdataframe.get(key) ParametersParameterDescription key Optional. A String or object representing the ...
❮ DataFrame Reference ExampleGet your own Python ServerReturn the sum of each row by applying a function:import pandas as pddef calc_sum(x):return x.sum()data = { "x": [50, 40, 30], "y": [300, 1112, 42]}df = pd.DataFrame(data)x = df.apply(calc_sum)print(x) ...
It can be a constant number like the one in the example, or it can be a list-like object like a list [15, 20] or a tuple {"points": 380, "total": 22}, or a Pandas Series or another DataFrame, that fits with the original DataFrame....
A Series with the skew values.If the level argument is specified, this method will return a DataFrame object.This function does NOT make changes to the original DataFrame object.❮ DataFrame Reference Track your progress - it's free! Log in Sign Up ...
ExampleGet your own Python ServerAdd the content of one DataFrame to another:import pandas as pddata1 = { "name": ["Sally", "Mary", "John"], "age": [50, 40, 30]}data2 = { "qualified": [True, False, False]}df1 = pd.DataFrame(data1)df2 = pd.DataFrame(data2) newdf = df...
ExampleGet your own Python ServerReplace the value 50 with the value 60, for the entire DataFrame:import pandas as pddata = { "name": ["Bill", "Bob", "Betty"], "age": [50, 50, 30], "qualified": [True, False, False]}df = pd.DataFrame(data)newdf = df.replace(50, 60) ...
Append a DataFrame at the end of another DataFrame:import pandas as pddata1 = { "age": [16, 14, 10], "qualified": [True, True, True]}df1 = pd.DataFrame(data1) data2 = { "age": [55, 40], "qualified": [True, False] }df2 = pd.DataFrame(data2)newdf = df1.append(df2)...